S-Sethisak/KhmerAsrDataset
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How to use S-Sethisak/whisper-small-kh-baseline with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="S-Sethisak/whisper-small-kh-baseline") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("S-Sethisak/whisper-small-kh-baseline")
model = AutoModelForSpeechSeq2Seq.from_pretrained("S-Sethisak/whisper-small-kh-baseline", device_map="auto")This model is a fine-tuned version of openai/whisper-small on the KhmerAsrDataset dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.5448 | 1.0 | 78 | 1.5003 | 100.0 | 137.4657 |
| 1.3444 | 2.0 | 156 | 1.3168 | 100.0 | 114.8952 |
| 1.2049 | 3.0 | 234 | 1.1834 | 100.0 | 100.3741 |
| 1.0807 | 4.0 | 312 | 1.0514 | 100.0 | 100.7715 |
| 0.8051 | 5.0 | 390 | 0.6328 | 100.0 | 71.2413 |
| 0.4002 | 6.0 | 468 | 0.3343 | 100.0 | 45.9660 |
| 0.233 | 7.0 | 546 | 0.2361 | 99.2793 | 39.8592 |
| 0.1433 | 8.0 | 624 | 0.1929 | 98.7387 | 34.2659 |
| 0.0852 | 9.0 | 702 | 0.1712 | 98.5586 | 32.4906 |
| 0.0542 | 10.0 | 780 | 0.1727 | 97.4775 | 31.2846 |
| 0.0306 | 11.0 | 858 | 0.1784 | 97.6577 | 30.4294 |
| 0.0187 | 12.0 | 936 | 0.1918 | 97.2973 | 30.3388 |
| 0.011 | 13.0 | 1014 | 0.2040 | 97.1171 | 30.3527 |
| 0.0077 | 14.0 | 1092 | 0.2102 | 96.3964 | 30.2784 |
| 0.0052 | 15.0 | 1170 | 0.2110 | 96.3964 | 29.5534 |
| 0.0036 | 16.0 | 1248 | 0.2198 | 96.0360 | 29.0770 |
| 0.0018 | 17.0 | 1326 | 0.2267 | 96.3964 | 28.9841 |
| 0.0013 | 18.0 | 1404 | 0.2316 | 96.9369 | 28.7842 |
| 0.0009 | 19.0 | 1482 | 0.2333 | 95.6757 | 28.4775 |
| 0.0006 | 20.0 | 1560 | 0.2368 | 96.5766 | 28.8981 |
| 0.0005 | 21.0 | 1638 | 0.2388 | 96.2162 | 28.7494 |
| 0.0004 | 22.0 | 1716 | 0.2410 | 96.0360 | 28.6680 |
| 0.0005 | 23.0 | 1794 | 0.2421 | 96.3964 | 28.7447 |
| 0.0004 | 24.0 | 1872 | 0.2428 | 96.3964 | 28.7819 |
| 0.0004 | 25.0 | 1950 | 0.2433 | 96.2162 | 28.7772 |
Base model
openai/whisper-small